Bottom trawling represents the most widespread anthropogenic physical disturbance to seafloor sediments on continental shelves. While trawling-induced changes to benthic ecology have been widely recognized, the impacts on long-term organic carbon storage in marine sediments remains uncertain. Here we combined datasets of sediment and bottom trawling for a heavily trawled region, the North Sea, to explore their potential mutual dependency. A pattern emerges when comparing the surface sediment organic carbon-to-mud ratio with the trawling intensity represented by the multi-year averaged swept area ratio. The organic carbon-to-mud ratio exhibits a systematic response to trawling where the swept area ratio is larger than 1 yr⁻¹. Three-dimensional physical–biogeochemical simulation results suggest that the observed pattern is attributed to the correlated dynamics of mud and organic carbon during transport and redeposition in response to trawling. Both gain and loss of sedimentary organic carbon may occur in weakly trawled areas, whereas a net reduction of sedimentary organic carbon is found in intensely trawled grounds. Cessation of trawling allows restoration of sedimentary carbon stock and benthic biomass, but their recovery occurs at different timescales. Our results point out a need for management of intensely trawled grounds to enhance the CO₂ sequestration capacity in shelf seas.

Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September–31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions.

On the role of soil moisture in the generation of heavy rainfall during the Oder flood event in July 1997

Long-term time series of coastal bathymetric data are indispensable for analysing morphological resilience to climate change. Despite the increasing popularity of utilizing high-resolution digital elevation models for coastal management, potential errors in analysing the long-term trend of bed elevation change from historical datasets have attracted little attention. Here, we demonstrate that inconsistency in the spatial resolution of small-scale topographic features characterized by sharp bathymetric gradients could produce errors in the mean elevation that in individual years could exceed the sea level change rate and result in a statistically significant bias in the trend of the mean elevation. Neglecting this inconsistency may lead to a misconception of coastal resilience to sea level rise. We provide an analytical method to identify such inconsistency in bathymetric datasets and a homogenization method to minimise the errors. Our methods are broadly applicable for analysing time series of geospatial data and quantitative assessment of data consistency.

Non-linear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross compartmental feedback loops in the earth system. These feedbacks are less well represented in traditional standalone atmosphere and ocean models on which many of today's regional climate assessments rely on (e.g. EuroCordex, NOSCCA, BACC II). This promotes the development of regional climate models for the Baltic Sea region by coupling different compartments of the earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed into the region by using prescribed boundary conditions, and thus, permit a higher degree of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress of model systems that allow two way communication between atmosphere and ocean models, models for the land surface including the terrestrial biosphere, as well as wave models at the air sea interface and hydrology models for water cycle closure. However, several processes that have so far mostly been realized by one way coupling such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g. aerosols) are not considered here. Compared to uncoupled standalone models, coupled earth system models models can modify mean near surface air temperatures locally up to several degrees compared to their standalone atmospheric counterparts using prescribed surface boundary conditions. Over open ocean areas, the representation of small scale oceanic processes such as vertical mixing, and sea ice dynamics appear essential to accurately resolve the air sea heat exchange in the Baltic Sea region and can only be provided by online coupled high resolution ocean models. In addition, the coupling of wave models at the ocean-atmosphere interface allows a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes like e.g. heavy precipitation, storms, or tropical nights, and appear to be sensitive to coupling. For the present-day climate, many coupled atmosphere-ocean and atmosphere-land surface models demonstrate added value with respect to single climate variables in particular when low quality boundary data were used in the respective standalone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models for closing the water cycle remains problematic as the accuracy of precipitation provided by the atmosphere models is in most cases insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments. Many regional standalone ocean and atmosphere models are tuned to well represent present day climatologies rather than accurately simulate climate change. More research is necessary about how the regional climate sensitivity (e.g. the models’ response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared to uncoupled ones.